Join Optum, a global leader dedicated to improving health outcomes through innovative technology. As a Manager in Data Science, you will be instrumental in leveraging AI, Machine Learning, and Generative AI, alongside Snowflake expertise, to tackle complex challenges and advance health optimization worldwide. Embrace a culture of inclusion and collaboration, working with talented peers to make a tangible impact.

This role offers a unique opportunity to drive advancements in AI and ML, contributing directly to our mission of helping millions live healthier lives. Be part of a dynamic team that connects people with essential care, pharmacy benefits, and data resources.

Translate intricate business challenges into actionable AI/ML, Generative AI, and Agentic AI solution designs. Conduct in-depth experimentation with cutting-edge AI technologies, including hands-on analysis of data to uncover critical insights. Develop and validate proof-of-concepts and prototypes, meticulously documenting findings, architectural recommendations, and reusable assets.

Spearhead the development of Generative AI solutions, employing techniques like RAG, advanced prompt engineering, and vector databases. Collaborate closely with cross-functional teams to refine requirements and ensure solutions deliver measurable business value. Effectively communicate complex technical results and their business impact to diverse stakeholders, accelerating AI adoption through repeatable patterns and efficient deployment strategies.

A Bachelor's degree in a relevant technical field such as Computer Science, Engineering, Data Science, or Mathematics is required, with a Master's degree being preferred. You should possess at least 8 years of experience in delivering Data Engineering or AI/ML solutions, with a strong track record in enterprise-scale AI initiatives.

Demonstrated hands-on expertise with Generative AI technologies, including LLMs, RAG, prompt engineering, embeddings, and vector databases, is essential. Familiarity with Agentic AI frameworks and orchestration platforms, coupled with robust programming skills in Python, SQL, and Snowflake, is expected. Experience with major cloud platforms like Azure, AWS, or GCP is also a key requirement. Proven ability to translate business needs into effective AI strategies and collaborate with engineering teams for successful production adoption is crucial.